A fault positioning method for long-distance conveying inspection robot

Abstract

This invention relates to the field of fault location technology and discloses a fault location method for a long-distance conveying inspection robot. The method includes: when the inspection robot performing long-distance conveying is detected to have reached an entrance equipped with an RFID tag, reading the RFID tag to determine the section of the long-distance conveying route to which the inspection robot belongs, and calculating the distance between the inspection robot and the entrance; acquiring an image of the idler roller taken by a camera mounted on the inspection robot, and using an image recognition algorithm to identify the idler roller code; when a fault signal is received, concatenating the section of the long-distance conveying route to which the inspection robot belongs, the distance between the inspection robot and the entrance, and the idler roller code identification result to obtain the position of the inspection robot in the long-distance conveying, and generating an alarm message. This invention combines RFID and visual recognition to accurately locate the inspection robot's position, improving positioning accuracy and thus improving fault handling efficiency.

Description

Technical Field

[0001] This invention relates to the field of fault location technology, and more specifically to a fault location method for a long-distance transport inspection robot. Background Technology

[0002] Currently, long-distance conveying systems are widely used in complex cross-regional material handling scenarios across multiple industries due to their advantages such as large capacity, long distance, low energy consumption, and continuous operation. Their lengths typically range from several kilometers to tens of kilometers, requiring crossings of highways, mountainous areas, and key structures such as trestle bridges and tunnels. Inspection robots, as commonly used automated inspection equipment, have emerged to address this need. When a malfunction occurs, most existing inspection robots rely on satellite positioning to obtain mileage, allowing personnel to reach the site for investigation based on blueprints. However, satellite positioning is only suitable for fully open-air conveying scenarios and cannot be applied to structures such as trestle bridges and tunnels. Summary of the Invention

[0003] This invention provides a fault location method for long-distance transport inspection robots, which solves the problem that existing technologies rely on satellite positioning and cannot be applied to structures such as trestle bridges and adits.

[0004] In a first aspect, the present invention provides a fault location method for a long-distance transport inspection robot, the method comprising:

[0005] When an inspection robot performing long-distance transport is detected to be running to an entrance marked with an RFID tag, the RFID tag is read to determine the section of the long-distance transport to which the inspection robot belongs, and the distance between the inspection robot and the entrance is calculated. The robot acquires images of idler rollers captured by a camera mounted on it, and uses image recognition algorithms to identify the idler roller codes from the images. When a fault signal is received, the inspection robot's location in the long-distance conveying section, the distance between the inspection robot and the entrance, and the roller coding identification result are spliced ​​together to obtain the inspection robot's location in the long-distance conveying. An alarm message is generated based on the inspection robot's location in the long-distance conveying.

[0006] This invention utilizes RFID technology for segment positioning to determine the segment to which the inspection robot belongs in long-distance transportation, replacing the traditional method of setting positioning points based on distance. This significantly reduces the number of positioning points, is not limited by the scene, calculates the distance between the inspection robot and the entrance, and initially realizes segment-based distance positioning. It uses image recognition algorithms to identify the idler roller code, and combines RFID and visual recognition to accurately locate the inspection robot's position, improving positioning accuracy and thus improving fault handling efficiency.

[0007] In one alternative implementation, the method further includes: RFID tags are installed at the entrance of long-distance transport sections, and tag information is written into the tags. These sections include adits and trestle bridges. The RFID reader on the inspection robot is used to read RFID tags.

[0008] This invention utilizes RFID tags to divide long-distance transportation into multiple segments, providing segment positioning for inspection robots. Compared with the traditional method of setting positioning points at preset distances, this reduces the workload of writing tag information and installing tags.

[0009] In one alternative implementation, reading the RFID tag to determine the section to which the inspection robot belongs during long-distance transport includes: Identify RFID tags and determine whether the flag bits of the RFID tags belong to preset flag bits. The preset flag bits consist of a variable name, a segment number, and a status value. If the flag bit of the RFID tag belongs to the preset flag bit, the segment to which the flag bit of the RFID tag belongs is determined according to the mapping relationship between the preset flag bit and the long-distance transportation segment.

[0010] This invention quickly filters invalid information read by the reader by comparing the flag bit of the identified RFID tag with a preset flag bit. If the flag bit of the RFID tag belongs to the preset flag bit, the corresponding segment is determined directly based on the mapping relationship between the preset flag bit and the long-distance transportation segment, making it suitable for long-distance transportation scenarios.

[0011] In one alternative implementation, calculating the distance between the inspection robot and the entrance includes: The timer starts when the inspection robot is detected to have moved to an entrance marked with an RFID tag; Detect the operating speed of the inspection robot; The product of the timing duration and the inspection robot's running speed is determined as the distance between the inspection robot and the entrance.

[0012] This invention calculates the distance between the inspection robot and the entrance using a simple logical relationship between distance, time, and speed, thereby reducing the computing power requirements of the edge processor and facilitating rapid fault location.

[0013] In one optional implementation, the idler code is identified from the idler image using an image recognition algorithm, including: Using idler roll coded images under different working conditions labeled with idler roll codes as the dataset, a target detection model was trained. The trained target detection model is used to locate the idler roller encoding region in the idler roller image; The character recognition model is used to identify the characters in the idler roll coding area as the idler roll code.

[0014] This invention utilizes a target detection model to locate the idler roll coding area, thereby reducing background interference on subsequent idler roll coding. It also uses a character recognition model to directly identify the idler roll code from the coding area, reducing computational load and effectively improving recognition efficiency.

[0015] In one optional implementation, when a fault signal is received, the location of the inspection robot in the long-distance transport section, the distance between the inspection robot and the entrance, and the idler roll coding identification result are concatenated to obtain the position of the inspection robot in the long-distance transport, including: When a fault signal is received from the inspection robot, or when a fault signal is sent by the inspection robot, the section to which the inspection robot belongs in long-distance transmission is determined as the first location information. The distance between the inspection robot and the entrance is determined as the second location information; The roller coding identification result is determined as the third location information; The combined result of the first, second, and third location information is used to determine the position of the inspection robot during long-distance transport.

[0016] This invention effectively combines RFID tags and visual recognition by splicing the inspection robot's section in long-distance transportation, the distance between the inspection robot and the entrance, and the roller coding identification results. This allows for precise positioning of the inspection robot in long-distance transportation, providing data for equipment maintenance and repair.

[0017] In an alternative implementation, after receiving a fault signal, the method further includes: Acquire images of the rollers near the position of the inspection robot during long-distance transport, captured by the camera mounted on the inspection robot. Based on images of the idlers near the location of the inspection robot during long-distance transport, a prompt message is generated.

[0018] This invention provides visual information for workers to locate fault points by displaying images of idlers near the location of the inspection robot during long-distance transport, thus reducing the difficulty for workers in finding fault points.

[0019] In a second aspect, the present invention provides a fault location device for a long-distance transport inspection robot, the device comprising: The RFID tag reading module is used to read the RFID tag when the inspection robot performing long-distance transportation runs to the entrance where the RFID tag is set, determine the section of the long-distance transportation to which the inspection robot belongs, and calculate the distance between the inspection robot and the entrance. The image recognition module is used to acquire images of the idler rollers taken by the camera mounted on the inspection robot, and to identify the idler roller code from the image using an image recognition algorithm; The fault location module is used to, when a fault signal is received, combine the inspection robot's section in the long-distance conveying process, the distance between the inspection robot and the entrance, and the roller coding identification result to obtain the inspection robot's position in the long-distance conveying process, and generate alarm information based on the inspection robot's position in the long-distance conveying process.

[0020] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the fault location method for a long-distance transport inspection robot described in the first aspect or any corresponding embodiment thereof.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the fault location method for a long-distance transport inspection robot described in the first aspect or any corresponding embodiment thereof. Attached Figure Description

[0022] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a fault location method for a long-distance transport inspection robot according to an embodiment of the present invention. Figure 2 This is a schematic diagram of label information according to an embodiment of the present invention; Figure 3 This is a structural block diagram of a fault location device for a long-distance transport inspection robot according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0026] According to an embodiment of the present invention, a fault location method for a long-distance transport inspection robot is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0027] This embodiment provides a fault location method for a long-distance transport inspection robot. Figure 1 This is a flowchart of a fault location method for a long-distance transport inspection robot according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps: Step S101: When the inspection robot performing long-distance transport is detected to have reached the entrance with an RFID tag, the RFID tag is read to determine the section of the long-distance transport to which the inspection robot belongs, and the distance between the inspection robot and the entrance is calculated.

[0028] In this embodiment of the invention, when the inspection robot performing long-distance transport reaches an entrance equipped with an RFID (Radio Frequency Identification) tag, the RFID tag is automatically read. Based on the RFID tag reading result, the segment to which the inspection robot belongs in the long-distance transport is determined, indicating which segment the inspection robot is currently in. To further determine the position of the inspection robot, the distance between the inspection robot and the entrance is calculated.

[0029] Step S102: Obtain images of idler rollers captured by the camera mounted on the inspection robot, and use an image recognition algorithm to identify the idler roller code from the idler roller images.

[0030] In this embodiment of the invention, the inspection robot is equipped with an industrial-grade camera. The camera can be fixed to the front or side of the robot, with the lens facing the idler roller bracket. Operators can remotely control the camera lens orientation to ensure the idler roller code is always centered in the captured image. The idler roller image captured by the camera is then processed by an edge processor using an image recognition algorithm to identify the idler roller code within the image. For example, the idler roller code is represented by "number#idler", such as "1200#idler".

[0031] Step S103: When a fault signal is received, the inspection robot's section in the long-distance conveying, the distance between the inspection robot and the entrance, and the roller coding identification result are spliced ​​together to obtain the position of the inspection robot in the long-distance conveying. An alarm message is generated based on the position of the inspection robot in the long-distance conveying.

[0032] In this embodiment of the invention, upon receiving a fault signal, the inspection robot's location within the long-distance transport section, the distance between the inspection robot and the entrance, and the idler roller's code identification result are concatenated. This, combined with RFID tags and visual recognition, enables fault location, revealing the inspection robot's position during the long-distance transport. An alarm message is generated based on the inspection robot's position during the long-distance transport, facilitating rapid fault location and timely fault handling by staff.

[0033] The fault location method for long-distance conveying inspection robots provided in this embodiment utilizes RFID technology for segment positioning to determine the segment to which the inspection robot belongs in the long-distance conveying process. This replaces the traditional method of setting positioning points based on distance, significantly reducing the number of positioning points and eliminating scene limitations. The method calculates the distance between the inspection robot and the entrance, initially achieving segment-based distance positioning. It uses image recognition algorithms to identify the idler roller code, thereby combining RFID and visual recognition to accurately locate the inspection robot's position, improving positioning accuracy and thus increasing fault handling efficiency.

[0034] This embodiment provides a fault location method for a long-distance transport inspection robot, the process of which includes the following steps: Step S201: Set up RFID tags at the entrance of the long-distance transport section and write tag information.

[0035] Step S202: Use the RFID reader mounted on the inspection robot to read the RFID tag.

[0036] In this embodiment of the invention, according to the actual process layout of long-distance transportation, RFID tags are set at the entrance of the section and tag information is written into the tags. This section includes, but is not limited to, important structures such as adits and trestle bridges. The tag information is used to identify the relative position of the section during long-distance transportation. For example, the tag information is as follows: Figure 2As shown.

[0037] The inspection robot is equipped with an industrial-grade RFID reader, which supports both contact and contactless reading, and uses the RFID reader to read RFID tags.

[0038] By using RFID tags to divide long-distance transportation into multiple segments, segment positioning is provided for the inspection robot. Compared with the traditional method of setting positioning points at preset distances, this reduces the workload of writing tag information and installing tags.

[0039] Step S203: When it is detected that the inspection robot performing long-distance transportation has run to the entrance with an RFID tag, the RFID tag is read to determine the section of the long-distance transportation to which the inspection robot belongs, and the distance between the inspection robot and the entrance is calculated.

[0040] Specifically, in step S203 above, reading the RFID tag to determine the section to which the inspection robot belongs in the long-distance transport includes: Step S2031: Identify the RFID tag and determine whether the flag bit of the RFID tag belongs to the preset flag bit; Step S2032: If the flag bit of the RFID tag belongs to the preset flag bit, then determine the segment to which the flag bit of the RFID tag belongs based on the mapping relationship between the preset flag bit and the long-distance transmission segment.

[0041] In this embodiment of the invention, the RFID reader mounted on the inspection robot reads the RFID tag, determines whether the flag bit of the RFID tag belongs to the preset flag bit according to the preset rules, and compares the flag bit of the RFID tag with the preset flag bit.

[0042] The preset flag consists of a variable name, a segment number, and a status value. For example, in the flag "flag_tun#2=1", the variable name is flag, the segment number is tun2, tun is the identifier of the tunnel, representing the second tunnel, and the status value is 1, where 1 represents valid and 0 represents invalid, that is, not entering the segment or having left the segment.

[0043] If the flag bit of the RFID tag does not belong to the preset flag bit, it indicates that the tag may be damaged or otherwise invalid, and the tag will be determined as invalid to avoid mislocation.

[0044] If the RFID tag's flag bit belongs to a preset flag bit, then query the mapping relationship between the preset flag bit and the long-distance transport section. This mapping relationship can be in the form of a pre-stored mapping table, etc., to find the section to which the RFID tag's flag bit belongs.

[0045] By comparing the flag bit of the identified RFID tag with the preset flag bit, invalid information read by the card reader is quickly filtered out. If the flag bit of the RFID tag belongs to the preset flag bit, the segment to which it belongs is directly determined according to the mapping relationship between the preset flag bit and the long-distance transportation segment, which is suitable for long-distance transportation scenarios.

[0046] Specifically, calculating the distance between the inspection robot and the entrance in step S203 above includes: Step S2033: When the inspection robot is detected to have moved to the entrance where the RFID tag is set, the timer starts; Step S2034: Detect the operating speed of the inspection robot; Step S2035: The product of the timing duration and the inspection robot's running speed is determined as the distance between the inspection robot and the entrance.

[0047] In this embodiment of the invention, the timing starts from the detection that the inspection robot has run to the entrance where the RFID tag is set. The timing is triggered by the timing module on the inspection robot and the running speed is triggered by the speed detection module on the inspection robot until the inspection robot runs to the entrance of the next section.

[0048] Calculate the distance between the inspection robot and the entrance. According to the basic logic of distance = speed × time, calculate the product of the timing duration t and the inspection robot's running speed v. Determine the product as the distance s between the inspection robot and the entrance, i.e., s = t × v.

[0049] By calculating the distance between the inspection robot and the entrance using a simple logical relationship between distance, time, and speed, the computing power requirements of the edge processor are reduced, making it easier to quickly locate fault points.

[0050] Step S204: Obtain images of the idler rollers captured by the camera mounted on the inspection robot, and use an image recognition algorithm to identify the idler roller code from the image.

[0051] Specifically, step S204 includes: Step S2041: Using the idler coded images under different working conditions labeled with idler coded as the dataset, train the target detection model; Step S2042: Use the trained target detection model to locate the idler coded region in the idler image; Step S2043: Use a character recognition model to identify the characters in the idler roll coding area as idler roll codes.

[0052] In this embodiment of the invention, idler roll coding images under different working conditions such as open air, strong sunlight, and windy and rainy weather are collected. Industrial-grade image annotation tools such as LabelImg are used to annotate the idler roll coding images. The dataset, consisting of these annotated idler roll coding images, is divided into training, validation, and test sets in a 7:2:1 ratio. YOLOv5s is selected as the object detection model for training. When the false detection rate of the object detection model reaches the required accuracy, the trained object detection model is used to scan the idler roll images and locate the idler roll coding region.

[0053] Since idler roll codes are usually numbers, a convolutional recurrent neural network combined with connection time-series classification is selected as a character recognition model. This model can identify the characters in the idler roll code area and determine the character as the idler roll code.

[0054] By using a target detection model to locate the idler roll coding area, the interference of the background on subsequent idler roll coding is reduced. The character recognition model is used to directly identify the idler roll code from the idler roll coding area, reducing the amount of computation and effectively improving the recognition efficiency.

[0055] Step S205: When a fault signal is received, the inspection robot's section in the long-distance conveying, the distance between the inspection robot and the entrance, and the roller coding identification result are spliced ​​together to obtain the position of the inspection robot in the long-distance conveying. An alarm message is generated based on the position of the inspection robot in the long-distance conveying.

[0056] Specifically, step S205 includes: Step S2051: When a fault signal is received from the inspection robot or a fault signal is sent by the inspection robot, the section to which the inspection robot belongs in long-distance transmission is determined as the first location information. Step S2052: Determine the distance between the inspection robot and the entrance as the second location information; Step S2053: The idler roll code recognition result is determined as the third position information; Step S2054: The splicing result of the first position information, the second position information, and the third position information is determined as the position of the inspection robot during long-distance transportation.

[0057] In this embodiment of the invention, when the inspection robot itself malfunctions, or when the inspection robot detects an environmental or equipment malfunction, the first location information is the section to which the inspection robot is located over a long distance, exemplarily, the first location information is inside tunnel #2. The distance between the inspection robot and the entrance is the second location information, exemplarily, the second location information is 34.56 meters from the entrance. The idler roller coding identification result is the third location information, exemplarily, the third location information is near idler roller #1200.

[0058] By splicing together the first, second, and third location information, the position of the inspection robot during long-distance transport is obtained as: "Inside the No. 2 adit, 34.56 meters from the entrance, near the No. 1200 idler roller". This allows staff to quickly locate the fault and handle it in a timely manner.

[0059] By combining the inspection robot's location within the long-distance transport section, the distance between the inspection robot and the entrance, and the roller coding identification results, and effectively integrating RFID tags and visual recognition, the position of the inspection robot during long-distance transport can be accurately located, providing data for equipment maintenance and repair.

[0060] In some alternative implementations, the method further includes: Step S206: Obtain images of the rollers near the position of the inspection robot during long-distance transport, captured by the camera mounted on the inspection robot. Step S207: Generate prompt information based on the image of the idler roller near the location of the inspection robot during long-distance transport.

[0061] In this embodiment of the invention, when a fault signal is received, the camera is triggered to take directional pictures, taking pictures of the inspection robot within a one-meter range in front, behind, left, and right of the inspection robot, with the inspection robot's position as the center. These pictures are images of the idlers near the inspection robot's position during long-distance transport, and prompt information is generated to display images of the idlers near the inspection robot's position during long-distance transport. This facilitates the staff to quickly locate the fault location and handle the fault in a timely manner.

[0062] The fault location method for long-distance conveying inspection robots provided in this embodiment provides a visual basis for workers to locate fault points by displaying images of idlers near the location of the inspection robot during long-distance conveying, thus reducing the difficulty for workers to find fault points.

[0063] This embodiment also provides a fault location device for a long-distance transport inspection robot. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0064] This embodiment provides a fault location device for a long-distance transport inspection robot, such as... Figure 3 As shown, it includes: The RFID tag reading module 301 is used to read the RFID tag when it detects that the inspection robot performing long-distance transportation has run to the entrance where the RFID tag is set, to determine the section of the long-distance transportation to which the inspection robot belongs, and to calculate the distance between the inspection robot and the entrance. The image recognition module 302 is used to acquire images of the idler rollers captured by the camera mounted on the inspection robot, and to identify the idler roller code from the idler roller images using an image recognition algorithm; The fault location module 303 is used to, when a fault signal is received, splice the inspection robot's section in the long-distance conveying, the distance between the inspection robot and the entrance, and the roller coding recognition result to obtain the position of the inspection robot in the long-distance conveying, and generate alarm information based on the position of the inspection robot in the long-distance conveying.

[0065] In some alternative embodiments, the device further includes: The module is used to set up RFID tags at the entrance of long-distance transport sections and write tag information. The sections include adits and trestle bridges. The reading module is used to read RFID tags using the RFID reader mounted on the inspection robot.

[0066] In some alternative implementations, the RFID tag reading module 301 includes: The judgment unit is used to identify RFID tags and determine whether the flag bits of the RFID tags belong to preset flag bits. The preset flag bits consist of variable name, segment number and status value. The segment determination unit is used to determine the segment to which the RFID tag's flag bit belongs based on the mapping relationship between the preset flag bit and the long-distance transport segment if the flag bit of the RFID tag belongs to the preset flag bit.

[0067] In some alternative implementations, the RFID tag reading module 301 includes: The timing unit is used to start timing when the inspection robot is detected to have moved to the entrance where an RFID tag is attached; The detection unit is used to detect the operating speed of the inspection robot; The distance determination unit is used to determine the distance between the inspection robot and the entrance by multiplying the timing duration and the inspection robot's running speed.

[0068] In some alternative implementations, the image recognition module 302 includes: The model training unit is used to train the target detection model using idler coded images under different working conditions labeled with idler coded as a dataset. The region localization unit is used to locate the coded region of the idler roller in the idler roller image using the trained target detection model; The recognition unit is used to identify the characters in the idler roll coding area as idler roll codes using a character recognition model.

[0069] In some alternative implementations, the fault location module 303 includes: The first determining unit is used to determine the section of long-distance transmission to which the inspection robot belongs as the first location information when it receives a fault signal from the inspection robot or a fault signal sent by the inspection robot. The second determining unit is used to determine the distance between the inspection robot and the entrance as the second position information; The third determining unit is used to determine the idler roll coding recognition result as the third position information; The fourth determining unit is used to determine the position of the inspection robot during long-distance transportation by splicing the first position information, the second position information, and the third position information.

[0070] In some alternative embodiments, the device further includes: The image acquisition module is used to acquire images of the rollers near the position of the inspection robot during long-distance transport, captured by the camera mounted on the inspection robot. The prompting module is used to generate prompting information based on images of the idlers near the location of the inspection robot during long-distance transport.

[0071] The fault location device for long-distance transport inspection robots provided in this embodiment of the invention can execute the fault location method for long-distance transport inspection robots provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0072] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0073] The following is a detailed reference. Figure 4 This diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 401, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 402 or a program loaded from memory 408 into random access memory (RAM) 403. The RAM 403 also stores various programs and data required for the operation of the electronic device. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0074] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 4 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0075] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 409, or installed from a memory 408, or installed from a ROM 402. When the computer program is executed by the processor 401, it performs the functions defined in the fault location method for a long-distance transport inspection robot according to embodiments of the present invention.

[0076] Figure 4 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0077] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the fault location method for a long-distance transport inspection robot shown in the above embodiments is implemented.

[0078] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0079] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and all such modifications and variations fall within the scope defined by the appended invention.

Claims

1. A fault location method for a long-distance transport inspection robot, characterized in that, The method includes: When an inspection robot performing long-distance transport is detected to be running to an entrance marked with an RFID tag, the RFID tag is read to determine the section of the long-distance transport to which the inspection robot belongs, and the distance between the inspection robot and the entrance is calculated. The robot acquires images of idler rollers captured by a camera mounted on it, and uses image recognition algorithms to identify the idler roller codes from the images. When a fault signal is received, the inspection robot's location in the long-distance conveying section, the distance between the inspection robot and the entrance, and the roller coding identification result are spliced ​​together to obtain the inspection robot's location in the long-distance conveying. An alarm message is generated based on the inspection robot's location in the long-distance conveying.

2. The method according to claim 1, characterized in that, The method further includes: RFID tags are installed at the entrance of long-distance transport sections, and tag information is written into the tags. The sections include adits and trestle bridges. The RFID reader on the inspection robot is used to read RFID tags.

3. The method according to claim 2, characterized in that, The process of reading RFID tags to determine the section of long-distance transport that the inspection robot belongs to includes: Identify RFID tags and determine whether the flag bits of the RFID tags belong to preset flag bits, wherein the preset flag bits consist of a variable name, a segment number, and a status value; If the flag bit of the RFID tag belongs to the preset flag bit, the segment to which the flag bit of the RFID tag belongs is determined according to the mapping relationship between the preset flag bit and the long-distance transportation segment.

4. The method according to claim 1, characterized in that, The calculation of the distance between the inspection robot and the entrance includes: The timer starts when the inspection robot is detected to have moved to an entrance marked with an RFID tag; Detect the operating speed of the inspection robot; The product of the timing duration and the inspection robot's running speed is determined as the distance between the inspection robot and the entrance.

5. The method according to claim 1, characterized in that, The method of identifying the idler code from the idler image using an image recognition algorithm includes: Using idler roll coded images under different working conditions labeled with idler roll codes as the dataset, a target detection model was trained. The trained target detection model is used to locate the idler roller encoding region in the idler roller image; The character recognition model is used to identify the characters in the idler roll coding area as the idler roll code.

6. The method according to claim 1, characterized in that, When a fault signal is received, the location of the inspection robot in the long-distance transport is obtained by concatenating the inspection robot's section in the long-distance transport, the distance between the inspection robot and the entrance, and the idler roller coding identification result, including: When a fault signal is received from the inspection robot, or when a fault signal is sent by the inspection robot, the section to which the inspection robot belongs in long-distance transmission is determined as the first location information. The distance between the inspection robot and the entrance is determined as the second location information; The roller coding identification result is determined as the third location information; The combined result of the first location information, the second location information, and the third location information is used to determine the position of the inspection robot during long-distance transport.

7. The method according to claim 1, characterized in that, After receiving a fault signal, the method further includes: Acquire images of the rollers near the position of the inspection robot during long-distance transport, captured by the camera mounted on the inspection robot. Based on images of the idlers near the location of the inspection robot during long-distance transport, a prompt message is generated.

8. A fault location device for a long-distance transport inspection robot, characterized in that, The device includes: The RFID tag reading module is used to read the RFID tag when the inspection robot performing long-distance transportation runs to the entrance where the RFID tag is set, determine the section of the long-distance transportation to which the inspection robot belongs, and calculate the distance between the inspection robot and the entrance. The image recognition module is used to acquire images of the idler rollers taken by the camera mounted on the inspection robot, and to identify the idler roller code from the image using an image recognition algorithm; The fault location module is used to, when a fault signal is received, combine the inspection robot's section in the long-distance conveying process, the distance between the inspection robot and the entrance, and the roller coding identification result to obtain the inspection robot's position in the long-distance conveying process, and generate alarm information based on the inspection robot's position in the long-distance conveying process.

9. An electronic device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the fault location method for a long-distance transport inspection robot as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the fault location method for a long-distance transport inspection robot as described in any one of claims 1 to 7.

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